Download Get PDF - OSA Publishing

yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Document related concepts

Nonlinear optics wikipedia, lookup

Atmospheric optics wikipedia, lookup

Optical rogue waves wikipedia, lookup

Night vision device wikipedia, lookup

Ultrafast laser spectroscopy wikipedia, lookup

Optical flat wikipedia, lookup

Chemical imaging wikipedia, lookup

Harold Hopkins (physicist) wikipedia, lookup

Optical coherence tomography wikipedia, lookup

Optical tweezers wikipedia, lookup

Scanning electrochemical microscopy wikipedia, lookup

Birefringence wikipedia, lookup

Magnetic circular dichroism wikipedia, lookup

Dispersion staining wikipedia, lookup

Rutherford backscattering spectrometry wikipedia, lookup

Nonimaging optics wikipedia, lookup

Refractive index wikipedia, lookup

3D optical data storage wikipedia, lookup

Photon scanning microscopy wikipedia, lookup

Vibrational analysis with scanning probe microscopy wikipedia, lookup

Scanning joule expansion microscopy wikipedia, lookup

Retroreflector wikipedia, lookup

Ultraviolet–visible spectroscopy wikipedia, lookup

Anti-reflective coating wikipedia, lookup

Silicon photonics wikipedia, lookup

Ellipsometry wikipedia, lookup

Surface plasmon resonance microscopy wikipedia, lookup

Research Article
Vol. 3, No. 2 / February 2016 / Optica
Surface plasmon resonance for characterization of
large-area atomic-layer graphene film
Department of Micro- and Nanosciences, Aalto University, Tietotie 3, FI-00076 Espoo, Finland
BioNavis Ltd., Elopellontie 3C, 33470 Ylöjärvi, Finland
e-mail: [email protected]
*Corresponding author: [email protected]
Received 31 August 2015; revised 22 December 2015; accepted 22 December 2015 (Doc. ID 249115); published 5 February 2016
Characterization of large-area thin films with atomic-scale resolution is challenging but in great demand for diverse
applications (e.g., nanotechnology and sensing). Here, we use the Surface Plasmon Resonance (SPR) method to characterize both the thickness and refractive index of chemical-vapor-deposition (CVD)-grown graphene films. The measured refractive index and extinction coefficient values of the CVD-grown graphene monolayer at 670 nm wavelength
are 3.135 and 0.897, respectively. Our results demonstrate that SPR shifts generated by graphene films are large
(i.e., ∼1°∕nm), almost tenfold larger than that observed in SPR measurements of organic monolayers. We find that
this significantly large SPR shift easily enables the thickness of a large area sample (i.e., ∼mm2 ) to be determined with
subnanometer-scale resolution. We show that the SPR method can identify thickness of different graphene layers and
give an estimate of ∼0.37 nm for the thickness of the CVD-grown graphene layer, which agrees extremely well with the
0.335 nm reported for layer-to-layer carbon atom distance of graphite crystals. Our results open the avenue to fast and
cost-effective simultaneous characterization of various parameters (including thickness and optical constants) of thin
films at the atomic-scale resolution. The presented characterization method can be applied both to physical characterizations of various two-dimensional layered materials as well as to the use of these layered materials for biosensing
applications as shown earlier, due to the favorable properties of graphene plasmons. © 2016 Optical Society of America
OCIS codes: (250.5403) Plasmonics; (160.4236) Nanomaterials; (240.6680) Surface plasmons; (000.2170) Equipment and techniques;
(310.3840) Materials and process characterization; (300.6550) Spectroscopy, visible.
Currently, graphene and other two-dimensional layered materials
are at the center of a significant research effort [1]. Graphene in
particular, the first two-dimensional atomic crystal, has attracted a
significant amount of interest in the past decade due to its many
unique physical properties (e.g., strong field effect with ultrahigh
electron mobility [2,3], high thermal conductivity [4], ultrafast
broadband optical response [5,6], and strong mechanical strength
and large elasticity [7]), which enable the realization of numerous
photonic and optoelectronic applications such as pulsed lasers
[5,8], modulators [9], photodetectors [10], and flexible screens
[11]. For all these applications, it is crucial to characterize the
properties (e.g., refractive index, thickness, etc.) of the used graphene films at both laboratory and mass-production scales. The
complex refractive index (RI) of graphene can be measured by
multiple methods, including spectroscopic ellipsometry and optical contrast analysis [12–16]. The current state of the art for
graphene RI determination, spectroscopic ellipsometry, showed
that it is possible to measure the optical constants together with
the thickness of graphene [12]. However, in those measurements,
the thickness of the graphene flakes given by the fitting procedure
2334-2536/16/020151-08$15/0$15.00 © 2016 Optical Society of America
deviated as much as 30%. On the other hand, the value of
0.335 nm for layer-to-layer carbon atom distance is commonly
used as a thickness of single-layer graphene in the literature.
Typical methods used for thickness characterization include
Raman spectroscopy measurements [17], optical contrast analysis
[18–20], and atomic force microscopy (AFM) [21–23]. Despite
their well-proven applicability, all these methods possess their
own limitations, with Raman being a rather indirect method,
optical contrast analysis (typically performed to flakes on silicon/
silicon oxide substrates) requiring certain silicon oxide thicknesses
to improve the optical contrast, and AFM systematically giving
too large thicknesses for exfoliated flakes. Furthermore, all of these
methods gather the information from a rather small measurement
area. Thus, there is still a great need for a fast, simple, and costeffective characterization method suitable for the measurement of
large-area samples.
Surface Plasmon Resonance (SPR) is a surface-sensitive optical
analysis technique capable of measuring ultrathin film properties
when full angular spectra are measured [24]. While the SPR
method is more typically associated with (bio)chemical interaction analysis, the method also shows excellent performance for
Research Article
characterizing nanoscale thin films [25], especially with the newly
arising multiple-wavelength methods in both wet and dry states
[26–28]. SPR is similar to ellipsometry in being a noninvasive
optical characterization technique, but SPR uses a noble metal
coating on sensors (typically gold) to create a highly sensitive
evanescent field at the metal surface, thus creating conditions
which are extremely sensitive to small changes in the close vicinity
of the surface (∼300 nm). Working with graphene by SPR and
several other graphene applications utilizing plasmonics has been
demonstrated and reviewed [1,29–40]. In particular, it has been
discussed that graphene surfaces on SPR sensors increase the sensor sensitivity; graphene has therefore been used as an alternative
chemical platform to the gold coatings [32,38,39]. However,
these works [29–40] have shown relatively little interest in using
the method to characterize the intrinsic film properties.
In this work, we present a simple, noninvasive SPR-based measurement method for characterization of the thickness and complex RI of chemical-vapor-deposition (CVD)-grown graphene
films with large area (i.e., ∼mm2 ). The obtained optical information (i.e., RI of 3.135 and extinction coefficient of 0.897) is
compared to the values measured by other groups which are commonly used in the literature. We also show that the SPR method
easily detects different graphene layer thicknesses and give an
estimate of ∼0.37 nm for the thickness of the CVD-grown graphene layer, which agrees extremely well with the reported
0.335 nm for layer-to-layer carbon atom distance of graphite
crystals. Furthermore, both of these measured parameters are obtained simultaneously from a single measurement without any
a priori information on these parameters. Thus, the presented
method can be applied both to graphene physical characterization
as well as to the use of graphene in biosensing applications as
presented earlier [1,29–40].
CVD-grown graphene layers were transferred onto SPR sensors
composed of optical glass, Cr adhesion layer, plasmonic Au coating, and an additional Al2 O3 thin-film top coating on plasmonic
Au coating labeled as Au and Al2 O3 sensors, respectively. CVDgrown graphene layers (fabricated as in Ref. [41]) were chosen due
to their uniformity, which allows us to use a simple wet transfer
process in the sample fabrication and prevents the complicated
alignment steps which would be required in the SPR measurements of micromechanically exfoliated graphene flakes. The graphene transfer was performed using a standard wet transfer
process as follows. First, polymethyl methacrylate (PMMA) polymer was coated onto the surface of CVD-grown graphene for protection. Afterward, copper substrate on which the graphene had
been grown was etched using ammonium peroxydisulfate. Then,
PMMA-coated graphene film was transferred onto the SPR sensor. In order to get rid of all the moisture, sensors were then
heated on a hotplate for 10 min at 150°C. Finally, the protective
PMMA film was removed after dissolving the sensors in acetone.
The transfer process was repeated three times, and therefore the
samples studied in this work were N layers of CVD-grown graphene (N 1, 2, and 3), with all of the different graphene layers
originating from the same growth run. Figure 1(a) shows an optical image taken from one of the characterized samples. The sensor cross-section is shown in the inset of Fig. 1(a). Two surface
Vol. 3, No. 2 / February 2016 / Optica
Fig. 1. (a) Optical image of one of the studied Al2 O3 sensors. Dashed
gray box outlines the 1L thick graphene film. Inset: schematically drawn
illustration showing the cross-section of the Al2 O3 sensor along the blue
line. Note that in the Au-coated sensors the Al2 O3 layer was missing.
(b) and (c) Schematic illustration of the Kretschmann configuration used
in the SPR measurements. During the measurements, the sensor is attached to the prism with the graphene layer on the opposite side of the
incident light (k). (b) When the projected wave vector (k x ) of the incident light does not match the wave vector of surface plasmon (k SP ), no
excitation occurs. (c) However, at a certain incident light angle (θ), the
projected wave vector of the incident light matches the wave vector of
surface plasmons, which depends on the wavelength of light and the
dielectric properties of the prism ε0 , metal layer ε2 , and the surrounding medium ε1 .
coatings (Au surface and Au surface Al2 O3 layer) were used to
examine the effect of the sensor surface material on the measurement results.
After each transfer process, SPR measurements were performed in Kretschmann configuration [see Figs. 1(b) and 1(c)]
using a BioNavis MP-SPR Navi 200-L apparatus equipped with
670 and 785 nm light sources. The measurements were performed at 25°C temperature in ambient air. The measurement
beam spot is approximately 0.5 mm in diameter, from which the
information is averaged. All the samples were measured as a reference before the graphene deposition and then measured again
after each consecutive layer deposition. The produced angular
spectra were then analyzed with the method described in the next
section of this work for the thickness and optical information.
Raman measurements were also performed by using a confocal Raman microscope (WITec alpha 300R) equipped with a
frequency-doubled Nd:YAG green laser (λ 532 nm) in order
to estimate the quality of transferred graphene films. The spectra
were acquired at room temperature in a backscattering geometry
using a 100 × microscope objective lens. The excitation power
was 1 mW. In addition, AFM measurements were performed
with NT-MDT NTegra Prima apparatus to estimate the height
of the transferred graphene layers. AFM imaging was performed
in semi-contact mode. The maximum scan area of the apparatus
was 13 μm × 13 μm.
Research Article
Vol. 3, No. 2 / February 2016 / Optica
The permittivity ε and the refractive index ñ of materials in their
complex forms are
ε ε 0 iε 0 0 ;
ñ n ik;
where ε 0 and ε 0 0 and n and k are the real and imaginary parts of
the complex permittivity and complex refractive index, respectively. Permittivity and refractive index have the following
ñ ε;
ε n2 k2 :
In order to obtain the complex refractive index (and also the
thickness) of the transferred graphene layer from the measured
permittivity, surface Plasmon resonance measurements were performed recording the reflected light intensity as a function of
incident light angle [as shown in Figs. 1(b) and 1(c)]. Surface plasmons are particle waves of the free electron plasma on a metal
surface, which can be excited by p-polarized light under the resonance condition [see the difference in Figs. 1(b) and 1(c)].
A theoretical description of the resonance condition can be obtained by solving the Maxwell equations for a multilayer optical
system [24], which provides the following mathematical solution
for the resonance condition:
ω pffiffiffiffiffi
ε1 ε2
ε0 sin θ ;
c ε1 ε2
where ω is the angular frequency of light, c is the speed of light in
vacuum, and ε0 , ε1 , and ε2 are the permittivities of the prism, SPR
metal layer, and the adjacent medium, respectively. As seen from
Eq. (5), measurement of only the SPR angle is not sufficient for the
unique determination of the complex permittivity and the thickness of the material. Similar reasoning was presented in Ref. [37]
which claimed that, in addition to the SPR angle detection, another independent observable is necessary for unique determination of the complex refractive index of graphene. However, in
addition to the location of the SPR angle, the shape of the spectrum also contains information regarding the material properties.
In fact, the attenuated total reflection intensity (TIR angle) data
(which was used as a second independent variable in Ref. [37]) can
also be found from the measured SPR curves. Therefore, in this
work, the complex permittivity and thickness of the graphene
were obtained simultaneously by solving a general problem for
a multilayer system. In practice, this is performed by BioNavis
LayerSolver software, which fits the solution of Maxwell equations
for a multilayer optical system to the measured reflectance spectrum obtained in Kretschmann configuration using a transfer matrix formalism of 2 × 2 matrices [24]. To increase the precision of
the measurement, background scans and fits for the noncoated
SPR sensors were performed before deposition. The optical information obtained from these fits is provided in the Supplement 1.
A. Raman Scattering
Prior to the SPR measurements, transferred graphene films were
examined by Raman scattering measurements to verify the quality
of the transfer process. The Raman scattering measurement results are shown in Fig. 2. The spectra show three different
Raman peaks in addition to the fluorescence signal from the
Bionavis SPR sensor, which has been subtracted from all the
shown spectra. Raman peaks located at the wavenumber of about
1335, 1580, and 2670 cm−1 can be attributed to D-, G-, and 2D
peaks of graphene, thereby verifying that graphene has been transferred onto the SPR sensor. These graphene Raman peaks originate from the in-plane lattice vibrations and have been reported to
occur from the A1g phonons, E2g phonons, and the overtones of
A 1g phonons of graphene, respectively [17,42]. Observation of
the D-peak in Raman measurements requires the presence of defects inside the graphene layer for its activation [17]. Therefore,
the intensity of the D-peak can be used as a measure of defect
density inside the graphene layer (i.e., the lower the intensity the
smaller the defect density) [42]. As observed, the D-peak intensity
increases with the increasing number of transfer processes which
can be attributed to the different types of defects caused by the
transfer processes. The presence of defects after the transfer process is expected as the wet transfer processes always affect the
quality of the graphene layers [43]. For instance, the transferred
graphene layer contains wrinkles and cracks whose density increases near the edges of the transferred graphene layer (discussed
later in this work). However, despite the slight increase in the Dpeak intensity, the intensity level is still low in all the samples,
which implies that the quality of the transferred graphene layers
is good on the SPR sensors. Lastly, it is worth noting that the
Raman spectra of the graphene layer on the copper growth template is significantly noisier than the spectra of the rest of the samples. The difference in the noise level is due to the increased
fluorescence signal from the copper substrate.
To gather information from the 2D and G peaks, we fit a
Lorenzian line shape to each Raman peak. Figures 2(b) and 2(c)
show the location of the 2D peak and the intensity ratio between
the G and 2D peaks as a function of the number of transfer processes. From this, we observe that 2D peaks at 2666 cm−1 ,
2676 cm−1 , and 2685 cm−1 for the 1L, 2L, and 3L thick samples,
Fig. 2. (a) Raman spectra of transferred graphene layers on Bionavis
Al2 O3 -coated SPR sensors: as-grown on Copper (green curve), 1-layer
(1L) graphene on SPR sensor (blue curve), 2-layer (2L) graphene on
SPR sensor (magenta curve), and 3-layer (3L) graphene on SPR sensor
(red curve). The fluorescence background has been subtracted from the
measured Raman spectra for easier comparison. (b) Integrated intensity
ratio between 2D and G peaks and (c) the 2D Raman peak position as a
function of the number of transfers.
Research Article
Vol. 3, No. 2 / February 2016 / Optica
Fig. 3. SPR curves on [(a) and (c)] Al2 O3 and [(b) and (d)] Au sensors. The fits (dashed red curves) have been performed separately for each
measurement. The laser excitation wavelength is 670 nm in (a) and (b) and 785 nm in (c) and (d).
respectively, redshift. The redshift of 2D peak is 19 cm−1 from 1
to 3 layers [Fig. 2(c)], and thus is similar to the behavior reported
for micromechanically exfoliated graphene flakes with increasing
graphene flake thickness [17]. The intensity ratio between the G
and 2D Raman peaks, on the other hand, increases from 0.42 to
1.78 with increasing number of layers [Fig. 2(b)], also comparable
to the behavior observed in Ref. [44] for different graphene flake
thicknesses. These results imply that the graphene layer thickness
increases with increasing number of graphene transfers and is
therefore expected.
B. Complex Refractive Index Measurement Using
Surface Plasmon Resonance
The optical constants of transferred graphene films were then
characterized by SPR. Examples of SPR curves of the transferred
graphene layers and the reference of bare Al2 O3 and bare Aucoated sensors are presented in Fig. 3. The SPR peaks show strong
shifts on both sensors. For instance, the resonance peak (black
curve) of the pure Al2 O3 sensor measured using 670 nm laser for
excitation is at 44.58°, while for 1L (blue curve), 2L (cyan curve),
and 3L (green curve) graphene samples it is at 44.93°, 45.19°, and
45.5°, respectively. For a repetition experiment of a different graphene batch on a different sensor, the background was 44.64° and
1L was 44.98° (See Supplement 1). As expected, the SPR angle
difference between the different sensors for both the background
and the monolayer graphene is extremely small (i.e., <0.1°), proving the good repeatability of the SPR-based characterization
method for large area samples. Furthermore, the SPR peak shift
is almost 1°/nm in both cases (assuming that the CVD graphene
layer thickness is 0.335 nm), and therefore almost ten times larger
than that of ∼0.15°∕nm for Langmuir–Blodgett (LB)-deposited
stearic acid monolayers [26] and nanofibrillar cellulose film [27].
This large SPR angle shift in graphene is due to the significantly
higher refractive index of graphene compared to that of the organic layers [26,27]. The results from the SPR angle comparison
are listed in Table 1. On the other hand, the resonance peak of the
sample with graphene layer on the Au sensor locates at 43.12° and
shifts slightly less than 0.6°/nm for the same incident wavelength.
Therefore, the Al2 O3 sensor gives a better contrast (change of
SPR peak) for the deposited graphene layer. To accurately obtain
the graphene refractive index and the layer thickness (which will
be discussed in the next section of this work) from the SPR results, we carried out the multiple-wavelength method analysis.
Thus, the SPR measurements were also performed using a
785 nm light for excitation [shown in Figs. 3(c) and 3(d)].
Reference [37] raised a question as to whether the SPR method
is able to uniquely distinguish the complex RI values of extremely
thin layers like graphene. However, based on the SPR spectra
shown in Fig. 3, this is not the case as all the shown SPR spectra
are distinguishable and result in unique fitting results. Indeed, all
the experimental results fit well with the theoretical simulation
(dashed red lines) obtained with the method described earlier.
Therefore, it seems that the experimental observations in
Ref. [37] (performed from the SPR angle data alone) might have
resulted from a significantly lower angular resolution, higher noise
than that obtained from a commercial dedicated SPR instrument
Table 1. SPR Angle Shifts of Various Materials
Graphene on Al2 O3 sensor
Graphene on Au sensor
Stearic acid monolayer
Nanocrystalline cellulose
Lipid bilayers (SiO2 sensor)
SPR Angle Shift (°/nm) Reference
This work
This work
Research Article
Vol. 3, No. 2 / February 2016 / Optica
with a angular step resolution of ∼0.005°, and from the fact that
their SPR data excluded the TIR region of the spectrum (i.e., the
angular range between 40° and 42° of the presented spectra in
Fig. 3). Due to these reasons, it was possible with the given
method to uniquely deduce the complex RI of graphene layers on
both sensors from a single measurement. The obtained optical
constants are presented in Table 2. SPR measurement reveals that
the RI of graphene on the Al2 O3 sensor is 3.135 for 1L graphene
and about 3.75 for 2L and 3L graphene samples at 670 nm.
Furthermore, the extinction coefficient (k) of 1L graphene is
0.897 at 670 nm, while for 2L and 3L graphene samples it decreases to 0.801 and 0.800, respectively. Moreover, comparable
values for RI and extinction coefficient to the values measured
with 670 nm laser are obtained when the SPR measurement is
performed with 785 nm laser, as shown in Table 2. This indicates
that RI and extinction coefficient are not changing significantly in
this wavelength range. Nearly negligible excitation light dependence on the RI agrees well with the literature, which shows almost
constant refractive index and slowly linearly increasing extinction
coefficient with increasing wavelength in the visible wavelength
range [12,13]. On the other hand, when the measurement is performed with graphene layers on the Au sensor, the values of 3.1
and 0.5 for refractive index and the extinction coefficient, respectively, are obtained for both 670 and 785 nm. It is worth noting
there were slight difficulties in performing the fitting-based analysis on Au coating, and therefore the RI error margins are higher in
this case. It is possible that the substrate smoothness (which differs
between the Au and Al2 O3 sensors) affects the fitting analysis.
As a matter of fact, in a work using spectroscopic ellipsometry,
the substrate smoothness was also proposed to be the dominating
factor for the higher error margins of the measured optical properties of graphene on SiO2 /silicon substrate than those measured on
extremely smooth amorphous quartz substrate [12]. Furthermore,
the interaction between the Au substrate and graphene may also
complicate the fitting analysis (e.g., electrons in plasmonic waves
escape to graphene layers as no dielectric Al2 O3 layer exists in
the Au sensors) and thus possibly contribute to the measurement
We compare the SPR measurement results to the literature
values measured by other groups using different measurement
methods (listed in Table 3). As mentioned, SPR measurement
reveals that the refractive index of 1L graphene on Al2 O3 sensor
is 3.135 at the wavelength of 670 nm, which is larger than (but in
the same magnitude with) the literature values which typically
range between 2.6 and 3 [12–16,37]. However, the measured
extinction coefficient of 0.897 is significantly smaller than the
values commonly used in the literature.
For instance, Ref. [12] reported an extinction coefficient value
of 1.5 for a micromechanically exfoliated single-layer graphene
Table 2. SPR Analysis Results of the Graphene Layers
670 nm
785 nm
670 and 785 nm
Al2 O3
Table 3. Comparison between the Complex Refractive
Index of Graphene Measured at 670 nm Using Different
3.135 0.897
SPR + attenuated 2.65
total reflection
Optical contrast 3
∼2.75 ∼1.50
2.886 1.634
This work
CVD graphene
on Al2 O3 sensor
CVD graphene on This work
Au sensor
CVD graphene
graphene flakes
graphene flakes
graphene flakes
graphene flakes
CVD graphene
Measurement has been performed using 630 nm wavelength.
using spectroscopic ellipsometry. This discrepancy could be because in the SPR measurements the incident and reflected light
do not pass the sample itself but instead SPR uses the evanescent
field in the measurement, so the field penetration direction is
perpendicular to the substrate. As opposed to this, in the spectroscopic ellipsometry and optical contrast measurements, the measurement beam passes through the sample, so the complex RI is a
component of both the planar and perpendicular RI. As the
graphene is clearly an anisotropic material in the plane and
perpendicular directions, it would be logical to have significant
difference in the complex RI also. When compared to the graphite
complex RI shown in Ref. [12], the RI has relatively small difference in the x-y-z directions (i.e., nx 2.86 and nz ∼ 2), but the
extinction coefficient has a large difference between the x and
z directions (i.e., kx ∼ 1.5 and kz ∼ 0). Therefore, it is likely that
the discrepancy in the measured extinction coefficient values is
larger than the discrepancy in the obtained RI values.
For the 2L and 3L graphene samples, the RI increases to 3.75.
This increase in RI could be attributed to the physical differences
of the layers, as it is well known that exfoliated single-layer
graphene has a different electrical structure than a multilayer graphene. However, compared to literature values of 2.886 and
1.634 for the RI and the extinction coefficient of bulk graphite,
respectively, these values are significantly larger [12,46]. This
could be a result of the anisotropy of graphene in the in-plane and
perpendicular directions as discussed earlier. However, it is probably more likely that the differences originate from the different
sample properties as the fabrication of the multilayer samples was
performed using a wet transfer process, and thus they possess a
completely different electrical and chemical structure (and also
RI) compared to perfectly assembled exfoliated multilayer graphene or graphite crystals.
C. Thickness Determination Using Surface Plasmon
When we measure the refractive index of graphene using our proposed SPR-based method, it simultaneously reveals the graphene
Research Article
layer thickness (also given in Table 2). Note that the fitted thickness is set to be the same for both incident wavelengths and thus is
obtained using multiple wavelength analysis. It is interesting to
note that the first graphene layer has a thickness of 0.82 nm
on the Al2 O3 substrate (and 1.07 nm on the Au substrate). This
is larger than expected based on the literature value of a single
layer of thick graphene, which is the same as the graphene–
graphene layer difference in graphite (i.e., 0.335 nm [47]). To
study this further, AFM measurements were performed to estimate the height of the 1L graphene edge (shown in Fig. 4). AFM
measurements reveal that 1L graphene has a thickness of about
5 nm. This estimate is also significantly larger than the literature
value of graphene thickness. As mentioned earlier, however, one
typical problem encountered when the thickness of graphene is
measured with AFM is that AFM systematically gives too large
layer thickness values [22,23]. In addition to this, AFM studies
reveal that the edge of the transferred graphene layer contains
wrinkles. This is no surprise because the wet transfer process is
far from a perfectly conformal process and can cause the edge
of the transferred graphene layer to be thicker. Due to all these
reasons, AFM is far from a perfect method to characterize the
height of graphene layers and thus new direct methods like
SPR measurement are needed.
One explanation for the higher-than-expected 1L graphene
thickness value is that the transferred graphene layer bridges gaps
of the sensor surface. Indeed, the AFM-measured substrate roughness of the Al2 O3 sensor is 1.85 nm. This behavior could be explained by the fact that the wet transfer process is not conformal
despite the large elasticity of the graphene. The same effect has
also been shown to contribute to LB-deposited monolayers [26].
Finally, it is also possible that the graphene spacing distance from
a dielectric layer is higher than that from the graphene–graphene
layer difference in graphite. If so, the typical behavior of AFM
thickness results being systematically thicker than expected could
also be partially explained by the same phenomenon. To gather
more evidence from that hypothesis, we plot the obtained
SPR thicknesses as a function of the number of transfer processes
(shown in Fig. 5). We also fit a linear curve, i.e., d l × N b,
to the obtained layer thicknesses in which l describes the thickness increase per each transfer process and b is a constant accounting for the possible gap between the graphene and the SPR sensor.
From that curve, it can be observed that the layer thickness l increases by 0.37 nm on Al2 O3 sensor after each transfer is performed, and therefore agrees well with the reported value of
0.335 nm for the graphene–graphene layer difference in graphite.
On the other hand, the graphene layer thickness increase per
transfer on the Au sensor is 0.31 nm, thus also agreeing well with
Fig. 4. (a) AFM image of the edge of the transferred graphene layer on
the Al2 O3 sensor and (b) the side profile along the blue line. The height
scale in the AFM image corresponds to a 40 nm difference.
Vol. 3, No. 2 / February 2016 / Optica
Fig. 5. Obtained layer thicknesses as a function of the number of
graphene transfers on the Al2 O3 -coated SPR sensors.
the reported value of 0.335 nm for graphene–graphene layer
thickness in graphite.
The values for the fitting constant b are 0.42 and 0.76 nm on
the Al2 O3 and Au sensors, respectively. If the gap, suggested by
the nonzero value of b, is originating from the substrate roughness
it should correlate with AFM measured surface roughness.
However, the AFM-measured substrate roughness of the Au sensor is 0.4 nm and is therefore smaller than that (1.85 nm) of the
Al2 O3 sensor. Thus, as a larger value of b is obtained from the Au
sensor, it seems that substrate roughness is not contributing to the
origin of the gap. On the other hand, the nonzero value of b may
also be affected by the surface residues created by the wet transfer
process. Nevertheless, it would then be likely that these residues
would be present in the interfaces of two- and three-layer-thick
samples. Therefore, the most probable explanation for the origin
of the gap seems to be that the interaction strengths between the
graphene layer and Al2 O3 or Au sensors are different and differ
from the graphene–graphene layer interaction of graphite, thereby
forcing the first graphene layer to be located further away from the
sensor surface [48].
We show that the SPR method can be used to characterize both
the thickness and refractive index of graphene. The measured refractive index and the extinction coefficient values of CVD-grown
graphene layers on the Al2 O3 sensor at 670 nm are 3.135 and
0.897, respectively, for 1L graphene and they differ with the
common literature values, which typically range between 2.6
and 3 and between 1.2 and 1.5, respectively. This discrepancy
is partially attributed to the anisotropy of graphene as the electric
field penetration direction in SPR measurements is perpendicular
to the substrate and therefore different from that used in more
typical approaches (such as spectroscopic ellipsometry and optical
contrast analysis). Furthermore, despite the small uncertainty in
terms of the absolute layer thickness for the 1L thick graphene
film, the SPR method can easily detect different graphene layer
thicknesses and gives an increase of 0.37 nm per layer. All in all,
the SPR peak shifts generated by each consecutive layer of graphene (∼1°∕nm) are almost ten-fold larger than those of organic
monolayers due to the high refractive index of graphene, allowing
us easily to determine the subnanometer layer thicknesses of large
area samples (∼mm2 ). As a result, our results open the avenue
for fast and cost-effective simultaneous characterization of the
Research Article
thickness and the optical constants of graphene (and other twodimensional layered materials). The presented characterization
method can therefore be applied both to the graphene physical
characterization as well as to the use of graphene in biosensing
applications as presented earlier [36].
Funding. Academy of Finland (284548, 285972); Seventh
Framework Programme (FP7) (631610).
Acknowledgment. The authors also thank Aalto
University and the Micronova Nanofabrication Centre for the
provision of facilities and technical support. H. J. thanks the
Jenny and Antti Wihuri Foundation for the financial support.
H. Y. acknowledges China Scholarship Council (CSC) for the
financial support.
See Supplement 1 for supporting content.
1. A. C. Ferrari, F. Bonaccorso, V. Fal’ko, K. S. Novoselov, S. Roche, P.
Bøggild, S. Borini, F. H. L. Koppens, V. Palermo, N. Pugno, J. A.
Garrido, R. Sordan, A. Bianco, L. Ballerini, M. Prato, E. Lidorikis, J.
Kivioja, C. Marinelli, T. Ryhänen, A. Morpurgo, J. N. Coleman, V.
Nicolosi, L. Colombo, A. Fert, M. Garcia-Hernandez, A. Bachtold, G. F.
Schneider, F. Guinea, C. Dekker, M. Barbone, Z. Sun, C. Galiotis, A. N.
Grigorenko, G. Konstantatos, A. Kis, M. Katsnelson, L. Vandersypen, A.
Loiseau, V. Morandi, D. Neumaier, E. Treossi, V. Pellegrini, M. Polini, A.
Tredicucci, G. M. Williams, B. H. Hong, J.-H. Ahn, J. M. Kim, H. Zirath,
B. J. van Wees, H. van der Zant, L. Occhipinti, A. Di Matteo, I. A. Kinloch,
T. Seyller, E. Quesnel, X. Feng, K. Teo, N. Rupesinghe, P. Hakonen,
S. R. T. Neil, Q. Tannock, T. Löfwander, and J. Kinaret, “Science and
technology roadmap for graphene, related two-dimensional crystals,
and hybrid systems,” Nanoscale 7, 4598–4810 (2015).
2. K. S. Novoselov, A. K. Geim, S. V. Morozov, D. Jiang, Y. Zhang, S. V.
Dubonos, I. V. Grigorieva, and A. A. Firsov, “Electric field effect in atomically thin carbon films,” Science 306, 666–669 (2004).
3. K. I. Bolotin, K. J. Sikes, Z. Jiang, M. Klima, G. Fudenberg, J. Hone, P.
Kim, and H. L. Stormer, “Ultrahigh electron mobility in suspended graphene,” Solid State Commun. 146, 351–355 (2008).
4. A. A. Balandin, S. Ghosh, W. Bao, I. Calizo, D. Teweldebrhan, F. Miao,
and C. N. Lau, “Superior thermal conductivity of single-layer graphene,”
Nano Lett. 8, 902–907 (2008).
5. Z. Sun, T. Hasan, F. Torrisi, D. Popa, G. Privitera, F. Wang, F.
Bonaccorso, D. M. Basko, and A. C. Ferrari, “Graphene mode-locked
ultrafast laser,” ACS Nano 4, 803–810 (2010).
6. F. Bonaccorso, Z. Sun, T. Hasan, and A. C. Ferrari, “Graphene photonics
and optoelectronics,” Nat. Photonics 4, 611–622 (2010).
7. C. Lee, X. Wei, J. W. Kysar, and J. Hone, “Measurement of the elastic
properties and intrinsic strength of monolayer graphene,” Science 321,
385–388 (2008).
8. A. Martinez and Z. Sun, “Nanotube and graphene saturable absorbers
for fibre lasers,” Nat. Photonics 7, 842–845 (2013).
9. M. Liu, X. Yin, E. Ulin-Avila, B. Geng, T. Zentgraf, L. Ju, F. Wang, and X.
Zhang, “A graphene-based broadband optical modulator,” Nature 474,
64–67 (2011).
10. F. Xia, T. Mueller, Y. Lin, A. Valdes-Garcia, and P. Avouris, “Ultrafast
graphene photodetector,” Nat. Nanotechnol. 4, 839–843 (2009).
11. S. Bae, H. Kim, Y. Lee, X. Xu, J. Park, Y. Zheng, J. Balakrishnan, T. Lei,
H. R. Kim, Y. Song, Y. J. Kim, K. S. Kim, B. Özyilmaz, J. H. Ahn, B. H.
Hong, and S. Iijima, “Roll-to-roll production of 30-inch graphene films for
transparent electrodes,” Nat. Nanotechnol. 5, 574–578 (2010).
12. V. G. Kravets, A. N. Grigorenko, R. R. Nair, P. Blake, S. Anissimova, K.
S. Novoselov, and A. K. Geim, “Spectroscopic ellipsometry of graphene
and an exciton-shifted van Hove peak in absorption,” Phys. Rev. B 81,
155413 (2010).
13. M. Bruna and S. Borini, “Optical constants of graphene layers in the
visible range,” Appl. Phys. Lett. 94, 031901 (2009).
Vol. 3, No. 2 / February 2016 / Optica
14. X. Wang, Y. P. Chen, and D. D. Nolte, “Strong anomalous optical
dispersion of graphene: complex refractive index measured by
Picometrology,” Opt. Express 16, 22105–22112 (2008).
15. J. W. Weber, V. E. Calado, and M. C. M. van de Sanden, “Optical
constants of graphene measured by spectroscopic ellipsometry,”
Appl. Phys. Lett. 97, 091904 (2010).
16. F. J. Nelson, V. K. Kamineni, T. Zhang, E. S. Comfort, J. U. Lee, and
A. C. Diebold, “Optical properties of large-area polycrystalline chemical
vapor deposited graphene by spectroscopic ellipsometry,” Appl. Phys.
Lett. 97, 253110 (2010).
17. A. C. Ferrari and D. M. Basko, “Raman spectroscopy as a versatile tool
for studying the properties of graphene,” Nat. Nanotechnol. 8, 235–246
18. L. Gao, W. Ren, F. Li, and H. M. Cheng, “Total color difference for rapid
and accurate identification of graphene,” ACS Nano 2, 1625–1633
19. Z. H. Ni, H. M. Wang, J. Kasim, H. M. Fan, T. Yu, Y. H. Wu, Y. P. Feng,
and Z. X. Shen, “Graphene thickness determination using reflection and
contrast spectroscopy,” Nano Lett. 7, 2758–2763 (2007).
20. P. Blake, E. W. Hill, A. H. Castro Neto, K. S. Novoselov, D. Jiang, R.
Yang, T. J. Booth, and A. K. Geim, “Making graphene visible,” Appl.
Phys. Lett. 91, 063124 (2007).
21. T. L. Burnett, R. Yakimova, and O. Kazakova, “Identification of epitaxial
graphene domains and adsorbed species in ambient conditions using
quantified topography measurements,” J. Appl. Phys. 112, 054308
22. K. S. Novoselov, D. Jiang, F. Schedin, T. J. Booth, V. V. Khotkevich,
S. V. Morozov, and A. K. Geim, “Two-dimensional atomic crystals,”
Proc. Natl. Acad. Sci. USA 102, 10451–10453 (2005).
23. E. A. Obraztsova, A. V. Osadchy, E. D. Obraztsova, S. Lefrant, and I. V.
Yaminsky, “Statistical analysis of atomic force microscopy and Raman
spectroscopy data for estimation of graphene layer numbers,” Phys.
Status Solidi B 245, 2055–2059 (2008).
24. I. Vikholm-Lundin and W. M. Albers, “Surface plasmon resonance on
nano-scale organic films,” in Nano-Bio-Sensing, S. Carrara, ed.
(Springer, 2010).
25. J. W. Sadowski, I. K. Korhonen, and J. P. Peltonen, “Characterization of
thin films and their structures in surface plasmon resonance measurements,” Opt. Eng. 34, 2581–2586 (1995).
26. N. Granqvist, H. Liang, T. Laurila, J. Sadowski, M. Yliperttula, and T.
Viitala, “Characterizing ultrathin and thick organic layers by surface plasmon resonance three-wavelength and waveguide mode analysis,”
Langmuir 29, 8561–8571 (2013).
27. K. S. Kontturi, E. Kontturi, and J. Laine, “Specific water uptake of thin
films from nanofibrillar cellulose,” J. Mater. Chem. A 1, 13655–13663
28. J. Malmström, M. K. Nieuwoudt, L. T. Strover, A. Hackett, O. Laita, M. A.
Brimble, D. E. Williams, and J. Travas-Sejdic, “Grafting from poly
(3, 4-ethylenedioxythiophene): a simple route to versatile electrically
addressable surfaces,” Macromolecules 46, 4955–4965 (2013).
29. J. Mertens, A. L. Eiden, D. O. Sigle, F. Huang, A. Lombardo, Z. Sun, R. S.
Sundaram, A. Colli, C. Tserkezis, J. Aizpurua, S. Milana, A. C. Ferrari,
and J. J. Baumberg, “Controlling subnanometer gaps in plasmonic
dimers using graphene,” Nano Lett. 13, 5033–5038 (2013).
30. A. N. Grigorenko, M. Polini, and K. S. Novoselov, “Graphene plasmonics,” Nat. Photonics 6, 749–758 (2012).
31. L. Ju, B. Geng, J. Horng, C. Girit, M. Martin, Z. Hao, H. A. Bechtel, X.
Liang, A. Zettl, Y. R. Shen, and F. Wang, “Graphene plasmonics for tunable terahertz metamaterials,” Nat. Nanotechnol. 6, 630–634 (2011).
32. F. H. L. Koppens, D. E. Chang, and F. J. Garcia de Abajo, “Graphene
plasmonics: a platform for strong light-matter interactions,” Nano Lett. 11,
3370–3377 (2011).
33. L. Wu, H. S. Chu, W. S. Koh, and E. P. Li, “Highly sensitive graphene
biosensors based on surface plasmon resonance,” Opt. Express 18,
14395–14400 (2010).
34. S. Szunerits, N. Maalouli, E. Wijaya, J. P. Vilcot, and R. Boukherroub,
“Recent advances in the development of graphene-based surface
plasmon resonance (SPR) interfaces,” Anal. Bioanal. Chem. 405,
1435–1443 (2013).
35. P. Subramanian, A. Lesniewski, I. Kaminska, A. Vlandas, A. Vasilescu,
J. Niedziolka-Jonsson, E. Pichonat, H. Happy, R. Boukherroub, and S.
Szunerits, “Lysozyme detection on aptamer functionalized graphenecoated SPR interfaces,” Biosens. Bioelectron. 50, 239–243 (2013).
Research Article
36. O. Salihoglu, S. Balci, and C. Kocabas, “Plasmon-polaritons on
graphene–metal surface and their use in biosensors,” Appl. Phys.
Lett. 100, 213110 (2012).
37. S. Cheon, K. D. Kihm, H. Kim, G. Lim, J. S. Park, and J. S. Lee, “How to
reliably determine the complex refractive index (RI) of graphene by using
two independent measurement constraints,” Sci. Rep. 4, 6364 (2014).
38. D. Rodrigo, O. Limaj, D. Janner, D. Etezadi, F. J. Garcia de Abajo,
V. Pruneri, and H. Altug, “Mid-infrared plasmonic biosensing with
graphene,” Science 349, 165–168 (2015).
39. V. G. Kravets, R. Jalil, Y.-J. Kim, D. Ansell, D. E. Aznakayeva, B.
Thackray, L. Britnell, B. D. Belle, F. Withers, I. P. Radko, Z. Han, S. I.
Bozhevolnyi, K. S. Novoselov, A. K. Geim, and A. N. Grigorenko,
“Graphene-protected copper and silver plasmonics,” Sci. Rep. 4, 5517
40. X. Yang, F. Zhai, H. Hu, M. Sun, Z. Sun, J. Chen, and Q. Dai, “Ultralong
lifetime plasmons on picosecond time scale enabled by hybrid plasmon–
phonon polaritons,” arXiv:1504.00195 (2015).
41. F. Bonaccorso, A. Lomabardo, T. Hasan, Z. Sun, L. Colombo, and A. C.
Ferrari, “Production and processing of graphene and 2d crystals,” Mater.
Today 15(12), 564–589 (2012).
Vol. 3, No. 2 / February 2016 / Optica
42. A. C. Ferrari, J. C. Meyer, V. Scardaci, C. Casiraghi, M. Lazzeri, F. Mauri,
S. Piscanec, D. Jiang, K. S. Novoselov, S. Roth, and A. K. Geim, “Raman
spectrum of graphene and graphene layers,” Phys. Rev. Lett. 97, 187401
43. X. Liang, B. A. Sperling, I. Calizo, G. Cheng, C. A. Hacker, Q. Zhang, Y.
Obeng, K. Yan, H. Peng, Q. Li, X. Zhu, H. Yuan, A. R. Hight Walker, Z.
Liu, L. Peng, and C. A. Richter, “Toward clean and crackless transfer of
graphene,” ACS Nano 5, 9144–9153 (2011).
44. Y. Y. Wang, Z. Ni, T. Yu, Z. X. Shen, H. Wang, Y. Wu, W. Chen, and A. T.
S. Wee, “Raman studies of monolayer graphene: the substrate effect,”
J. Phys. Chem. C 112, 10637–10640 (2008).
45. N. Granqvist, M. Yliperttula, S. Valimäki, P. Pulkkinen, H. Tenhu, and T.
Viitala, “Control of the morphology of lipid layers by substrate surface
chemistry,” Langmuir 30, 2799–2809 (2014).
46. A. B. Djurišić and E. H. Li, “Optical properties of graphite,” J. Appl. Phys.
85, 7404–7410 (1999).
47. B. T. Kelly, Physics of Graphite (Applied Science, 1981).
48. J. C. Love, L. A. Estroff, J. K. Kriebel, R. G. Nuzzo, and G. M. Whitesides,
“Self-assembled monolayers of thiolates on metals as a form of nanotechnology,” Chem. Rev. 105, 1103–1170 (2005).